Programme And Module Handbook
Course Details in 2025/26 Session

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Module Title LH Natural Language Processing
SchoolComputer Science
Department Computer Science
Module Code 06 37810
Module Lead Dr Mark Lee
Level Honours Level
Credits 20
Semester Semester 2
Pre-requisites LH Neural Computation - (06 32167)
Restrictions None
Contact Hours Lecture-33 hours
Guided independent study-167 hours
Total: 200 hours
Description Natural Language Processing enables computers to understand and reason about human languages such as English and has resulted in many exciting technologies such as conversational assistants, machine translation and (intelligent) internet search. This module would provide the theoretical foundations of NLP as well as applied techniques for extracting and reasoning about information from text.

The module explores three major themes:
Computational Models of human cognition such as memory, attention and psycholinguisticsSymbolic AI methods for processing language such as automated reasoning, planning, parsing of grammar, and conversational systems.

Statistical Models of Language including the use of machine learning to infer structure and meaning.
Learning Outcomes By the end of the module students should be able to:
  • Demonstrate an understanding of the major topics in Natural Language Processing
  • Understand the role of machine learning techniques in widening the coverage of NLP systems
  • Demonstrate an ability to apply knowledge-based and statistical techniques to real-world NLP problems
Assessment 37810-01 : Continuous Assessment : Coursework (20%)
37810-02 : Examination : Exam (Centrally Timetabled) - Written Unseen (80%)
Assessment Methods & Exceptions Assessment:

2 hr Examination (80%)
,Continuous Assessment (20%)


2 hr Examination (100%)
Reading List